Department of Electrical and Information Engineering

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    DEVELOPMENT OF AN ADAPTIVE VIRTUAL SYNCHRONOUS GENERATOR-BASED FREQUENCY CONTROL STRATEGY FOR HYBRID AC/DC MICROGRIDS
    (Covenant University, Ota, 2026-08) BELLO, Abiodun Yusuff; Covenant University, Dissertation
    The rapid transition to sustainable energy sources has led to the large-scale integration of renewable energy technologies such as solar and wind power into today's power grids. These renewable resources do not generate mechanical inertia like conventional synchronous generators; the grids increasingly risk becoming more unstable when frequencies drop. This is particularly challenging in hybrid AC/DC microgrids, where both AC frequency and DC-link voltage must be controlled simultaneously, and Virtual Synchronous Generator (VSG) control is an efficient solution. A control algorithm is implemented to make inverters behave like the inertial and damping characteristics of a synchronous machine. However, most current VSGbased schemes use fixed values for virtual inertia and damping, which fail under varying disturbance magnitudes. Deviating from a fixed inertia value, this research designed and tested an adaptive VSG-based frequency control method for an isolated hybrid AC/DC Microgrid in MATLAB/Simulink R2024b. Real-time frequency deviation and rate of change of frequency (RoCoF) parameters are used to adapt the VSG frequency control. The interlinking converter was tested under two different load disturbances of opposite nature of 2s, i.e., load decrease and load increase, and compared with the conventional fixed-inertia controller (H = 0.5 kg·m²). In both scenarios, the inverter was found to be electrically stable, and the adaptive inertia was found to be sensitive to each disturbance, showing that it changes its operating condition from 0.5 kg·m² to approximately 0.6 kg·m² instead of remaining fixed; importantly, in each load change scenario, it was observed that the adaptive VSG performed a reduced transient frequency deviation than the conventional controller.
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    DEVELOPMENT OF A REGENERATIVE BRAKING MODEL USING MAMDANI FUZZY LOGIC CONTROL FOR BATTERY MANAGEMENT IN ELECTRIC VEHICLES
    (Covenant University, Ota, 2026-08) BELLO, Esosasere Victory; Covenant University, Dissertation
    Electric vehicles are one of the key options on the pathway to sustainable mobility, however, optimising the energy efficiency of EVs is a central engineering challenge. One of the most promising methods for extending driving range to the battery onboard a vehicle is regenerative braking, which recycles kinetic energy when the vehicle brakes, but causes transient charging currents and power peaks for the BMS to manage safely. How and when the braking torque is applied to regeneration is thus a key control strategy in energy performance and battery health. This work presents and tests a full regenerative braking model with battery management for EVs based on a Mamdani fuzzy logic controller that was selected by a principle-based and evidence-based comparative screening that compared this controller with a Takagi-Sugeno alternative. Both drivers took the full 1180-second New European Driving Cycle (NEDC). The comparative screening results have shown that the Mamdani controller has lower total battery SOC depletion for the entire NEDC (0.65%) when compared to Takagi-Sugeno (0.70%), which makes it the controller used for the entire model. The selected Mamdani-controlled model was evaluated with regards to the measured engineering outputs and showed: a net consumption of battery energy of 292.5 Wh over the complete NEDC test; an estimated regenerative energy of 73 Wh (ca. 20% regenerative efficiency) over the whole NEDC test; armature current between 0–35 A; stable motor speed tracking of the NEDC reference profile in both the urban (0–680 s) and the extra-urban (681–1180 s) part of the test.